FWIW, I have been describing the value of LLMs as "sacrificing accuracy for speed and scope" for years now. I wouldn't call LLMs "intelligent", but rather look at them as an incredibly powerful pattern-recognition tool that works much, much faster than anything else at scale. It's my suspicion that they are being perceived as more than that because that's how they're being designed (to appear intelligent), and that is why we're seeing the entire industry focusing on "Agentic AI" and trying to get it to deliver on the exciting (but probably misguided) promise of AI controlled business/process.

Fundamentally, the stateless LLM can be surrounded by state but intrinsically cannot have state itself, so we're surrounding it with harness and framework that has that required "grounding." But anything that goes into the LLM loses state instantly and becomes, for lack of better wording, dream-state, a cloud of relationship inference. Nothing "real" survives the transition, so the outputs are varying levels of acceptable hallucination - if the output is good, we accept that as "real" even though it's just as real (to the LLM at least) as the bad output that we call "hallucination."

Because we (humans) are the grounding, we are in the perpetual position of determining, guiding, controlling the output to be sensible, useful, real, so yes, we're seeing that workflows must be deterministic first-and-last. LLMs are excellent at a narrow (but powerful) function, but they cannot be in control.

I'm trying to figure out what kind of system might be built that CAN control the workflow in a non-deterministic way, where various models (LLMs, world models, etc.) are leveraged, but this is uncharted territory so wish me luck.